The Application of Improved GM(1,1) in Power Load Forecasting

Cheng Xiang Fan; Kai Quan Shi; Ke Jun Li

doi:10.4028/www.scientific.net/AMR.108-111.151

Paper Titles

Bioprocess Soft Sensing Based on Multiple Kernel Support Vector Machine
p.129

A Secure Networking Architecture for the Internet of Things
p.135

Wavelet-Based Image De-Noising Method for Forest Wildfire
p.141

Design on Environment Monitoring System for Greenhouse Based on Wireless Sensor Network
p.145

The Application of Improved GM(1,1) in Power Load Forecasting
p.151

China's Small Hydropower CDM Projects Development on Low-Carbon Economy Era
p.156

A Scientific Strategy Research of the Coordinated Development between Intrinsic Safety and Clean Production Technologies under the Green Chemistry Framework
p.162

Analysis and Research of Financial Network Security Architecture
p.168

Rate Distortion Model Analysis for H.264/AVC Video Coding
p.172

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 108-111The Application of Improved GM(1,1) in Power Load...

The Application of Improved GM(1,1) in Power Load Forecasting

Abstract:

The forecasting precision of GM(1,1) is very low, when the data sequence is not smooth. The logarithm smoothing is used for the original data sequence. Considering the low precision caused by overlarge and forecasting gray interval for gray modeling, A novel method is proposed for power load forecasting: weighted forecasting method of gray related degree with revised parameter and logarithm smoothing. The method can make various factors weaken or counteracted and prevent the forecasting data from too fast increasing. The proposed model is demonstrated by a test in a certain area. The result shows that the method is effective both in theory and in practice.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 108-111)

Pages:

151-155

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.108-111.151

Citation:

Cite this paper

Online since:

May 2010

Authors:

Cheng Xiang Fan, Kai Quan Shi, Ke Jun Li

Keywords:

Gray Related Degree, Improved GM(1,1), Logarithm Smoothing, Revised Parameter

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Niu Dongxiao, Zhang Wenwen etc, Adustment Gray Model for load Forecasting of Power Systems, The Journal of Gray System, 1994(6), 127-134.

Google Scholar

[2] Liu Sifeng, Feng Qiming, Dang Yaoguo, Gray System Theory and its Application[M], Beijing, Science Press, (1999).

Google Scholar

[3] Deng Julong，Properties of Multivariable Gray Model GM(1，N)，The Journal of Gray System， 1989，Vol. 1，No. 1，25-41.

Google Scholar

[4] Deng Julong, Gray Differential Equation, The Journal of Gray System, Vol. 5, No. 1, 1-14, (1993).

Google Scholar

[5] ZHU Chang-qing, WANG Xiu-he, ZHANG Xin, SHEN Ning, A Novel Load Forecast Method Based on Gray Relational Weighing Combination Model, Proceeding of the CSU-EPSA, 2006, 18(2), 79-81.

Google Scholar

[6] Chen Yaokai and Xuerui, Gray Relational Analysis on Serum Markers of Liver Fibrosis, The Journal of Gray System, Vol. 7, No. 1, 63-68, (1995).

Google Scholar

[7] Deng Julong，Introduction to Gray System Theory，The Journal of Gray System，1989，Vol. 1， No. 1，1-24.

Google Scholar